A method and device for ranking customer scores, a computer device and a storage medium

Abstract

The application relates to the field of processing a large amount of data, and discloses a method and device for ranking customer scores based on big data analysis, a computer device and a storage medium. The method includes: assigning customer scores to a plurality of groups that meet the score range, each of the groups corresponds to a score interval, and the plurality of groups are sorted according to a preset sorting rule according to the size of the corresponding score interval, wherein the score intervals corresponding to the plurality of groups are score intervals with continuous scoresand no coincidence; sorting the customer scores in each group according to the collation rule in a multi-threaded parallel processing manner; and combining a plurality of groups sorted by customer scores within the group are ed according to the sorting rules to generate a customer score sorting list. The present application divides all the scores into a plurality of groups according to an interval, and a plurality of servers respectively sort the plurality of groups simultaneously to reduce the sorting time.

Description

technical field [0001] This application relates to the field of processing a large amount of data, in particular to a method, device, computer equipment and storage medium for sorting customer scores. Background technique [0002] At present, there is a large amount of customer information in the life insurance database. When ranking customers after scoring them in different dimensions, due to the large number of customers, some databases even have hundreds of millions of customers, the ranking costs The time is relatively long. [0003] At present, when sorting a large amount of data, the merge sort method is generally used. However, when the merge sort algorithm integrates the data, the operation is relatively cumbersome in the final merge sort, and it needs to have very large requirements on the server. Generally, it takes a lot of time for the server to sort a large amount of data, and the sorted list is obtained. slower. [0004] Therefore, providing a new method for...

AI Technical Summary

Problems solved by technology

However, when the merge sort algorithm integrates the data, the operation is relatively cumbersome in the final merge sort, which requires a very large requirement on the server. It takes a lot of time for the general server to sort a large amount of data, and the sorted list is obtained. slower

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